Analyzing factors affecting positivity in drive-through COVID-19 testing: a cross-sectional study.

BACKGROUND: Demand for COVID-19 testing prompted the implementation of drive-through testing systems. However, limited research has examined factors influencing testing positivity in this setting. METHODS: From October 2020 to March 2023, a total of 1,341 patients, along with their clinical information, were referred from local clinics to the Sasebo City COVID-19 drive-through PCR center for testing. Association between clinical information or factors related to the drive-through center and testing results was analyzed by Fisher's exact test and logistic regression models. RESULTS: Individuals testing positive exhibited higher frequencies of upper respiratory symptoms; cough (OR 1.5 (95% CI 1.2-1.8), p < 0.001, q = 0.005), sore throat (OR 2.4 (95% CI 1.9-3.0), p < 0.001, q < 0.001), runny nose (OR 1.4 (95% CI 1.1-1.8), p = 0.002, q = 0.009), and systemic symptoms; fever (OR 1.5 (95% CI 1.1-2.0), p = 0.006, q = 0.02), headache (OR 1.9 (95% CI 1.4-2.5), p < 0.001, q < 0.001), and joint pain (OR 2.7 (95% CI 1.8-4.1), p < 0.001, q < 0.001). Conversely, gastrointestinal symptoms; diarrhea (OR 0.2 (95% CI 0.1-0.4), p < 0.001, q < 0.001) and nausea (OR 0.3 (95% CI 0.1-0.6), p < 0.001, q < 0.001) were less prevalent among positives. During omicron strain predominant period, higher testing positivity rate (OR 20 (95% CI 13-31), p < 0.001) and shorter period from symptom onset to testing (3.2 vs. 6.0 days, p < 0.001) were observed compared to pre-omicron period. Besides symptoms, contact history with infected persons at home (OR 4.5 (95% CI 3.1-6.5), p < 0.001, q < 0.001) and in office or school (OR 2.9 (95% CI 2.1-4.1), p < 0.001, q < 0.001), as well as the number of sample collection experiences by collectors (B 7.2 (95% CI 2.8-12), p = 0.002) were also associated with testing results. CONCLUSIONS: These findings underscore the importance of factors related to drive-through centers, especially contact history interviews and sample collection skills, for achieving higher rates of COVID-19 testing positivity. They also contribute to enhanced preparedness for next infectious disease pandemics.

Conceptualizing National Advisory Boards in primary care research: application to the Two in One HIV and COVID screening and testing model.

The authors report on their development of a National Advisory Board (NAB) to guide a funded project: Two in One: HIV + COVID-19 Screening and Testing Model. This project aimed to improve primary care practitioners' capacity to routinize HIV, PrEP/PEP, and COVID-19 vaccine screenings for all their patients while relying on culturally responsive communication with their minoritized patients. To approach their monumental research and education tasks, they created a NAB, drawing from the literature on advisory boards to (a) promote board member engagement and (b) progress successfully through the six stages suggested for successful advisory boards. A midpoint survey and final focus groups with NAB members indicated mixed levels of engagement, a sense of time and work being valued, and pride in the media and academic reach of the project. The authors offer considerations for others considering forming a NAB to guide primary care research and interventions.

Evaluations of modes of pooling specimens for COVID-19 screened by quantitative PCR and droplet digital PCR.

Though pooling samples for SARS-CoV-2 detection has effectively met the need for rapid diagnostic and screening tests, many factors can influence the sensitivity of a pooled test. In this study, we conducted a simulation experiment to evaluate modes of pooling specimens and aimed at formulating an optimal pooling strategy. We focussed on the type of swab, their solvent adsorption ability, pool size, pooling volume, and different factors affecting the quality of preserving RNA by different virus solutions. Both quantitative PCR and digital PCR were used to evaluate the sampling performance. In addition, we determined the detection limit by sampling which is simulated from the virus of different titers and evaluated the effect of sample-storage conditions by determining the viral load after storage. We found that flocked swabs were better than fibre swabs. The RNA-preserving ability of the non-inactivating virus solution was slightly better than that of the inactivating virus solution. The optimal pooling strategy was a pool size of 10 samples in a total volume of 9 mL. Storing the collected samples at 4 °C or 25 °C for up to 48 h had little effect on the detection sensitivity. Further, we observed that our optimal pooling strategy performed equally well as the single-tube test did. In clinical applications, we recommend adopting this pooling strategy for low-risk populations to improve screening efficiency and shape future strategies for detecting and managing other respiratory pathogens, thus contributing to preparedness for future public health challenges.

A joint penalized spline smoothing model for the number of positive and negative COVID-19 tests.

One of the key tools to understand and reduce the spread of the SARS-CoV-2 virus is testing. The total number of tests, the number of positive tests, the number of negative tests, and the positivity rate are interconnected indicators and vary with time. To better understand the relationship between these indicators, against the background of an evolving pandemic, the association between the number of positive tests and the number of negative tests is studied using a joint modeling approach. All countries in the European Union, Switzerland, the United Kingdom, and Norway are included in the analysis. We propose a joint penalized spline model in which the penalized spline is reparameterized as a linear mixed model. The model allows for flexible trajectories by smoothing the country-specific deviations from the overall penalized spline and accounts for heteroscedasticity by allowing the autocorrelation parameters and residual variances to vary among countries. The association between the number of positive tests and the number of negative tests is derived from the joint distribution for the random intercepts and slopes. The correlation between the random intercepts and the correlation between the random slopes were both positive. This suggests that, when countries increase their testing capacity, both the number of positive tests and negative tests will increase. A significant correlation was found between the random intercepts, but the correlation between the random slopes was not significant due to a wide credible interval.

New framework to assess tracing and testing based on South Korea's response to COVID-19.

South Korea's remarkable success in controlling the spread of COVID-19 during the pre-Omicron period was based on extensive contact tracing and large-scale testing. Here we suggest a general criterion for tracing and testing based on South Korea's experience, and propose a new framework to assess tracing and testing. We reviewed papers on South Korea's response to COVID-19 to capture its concept of tracing and testing. South Korea expanded its testing capabilities to enable group tracing combined with preemptive testing, and to conduct open testing. According to our proposed model, COVID-19 cases are classified into 4 types: confirmed in quarantine, source known, source unknown, and unidentified. The proportion of the first two case types among confirmed cases is defined as "traced proportion", and used as the indicator of tracing and testing effectiveness. In conclusion, South Korea successfully suppressed COVID-19 transmission by maintaining a high traced proportion (> 60%) using group tracing in conjunction with preemptive testing as a complementary strategy to traditional contact tracing.

Assessing SARS-CoV-2 Testing Adherence in a University Town: Recurrent Event Modeling Analysis.

BACKGROUND: Healthy Davis Together was a program launched in September 2020 in the city of Davis, California, to mitigate the spread of COVID-19 and facilitate the return to normalcy. The program involved multiple interventions, including free saliva-based asymptomatic testing, targeted communication campaigns, education efforts, and distribution of personal protective equipment, community partnerships, and investments in the local economy. OBJECTIVE: This study identified demographic characteristics of individuals that underwent testing and assessed adherence to testing over time in a community pandemic-response program launched in a college town in California, United States. METHODS: This study outlines overall testing engagement, identifies demographic characteristics of participants, and evaluates testing participation changes over 4 periods of the COVID-19 pandemic, distinguished by the dominant variants Delta and Omicron. Additionally, a recurrent model is employed to explore testing patterns based on the participants' frequency, timing, and demographic characteristics. RESULTS: A total of 770,165 tests were performed between November 18, 2020, and June 30, 2022, among 89,924 (41.1% of total population) residents of Yolo County, with significant participation from racially or ethnically diverse participants and across age groups. Most positive cases (6351 of total) and highest daily participation (895 per 100,000 population) were during the Omicron period. There were some gender and age-related differences in the pattern of recurrent COVID-19 testing. Men were slightly less likely (hazard ratio [HR] 0.969, 95% CI 0.943-0.996) to be retested and more likely (HR 1.104, 95% CI 1.075-1.134) to stop testing altogether than women. People aged between 20 and 34 years were less likely to be retested (HR 0.861, 95% CI 0.828-0.895) and more likely to stop testing altogether (HR 2.617, 95% CI 2.538-2.699). However, older age groups were less likely to stop testing, especially those aged between 65-74 years and 75-84 years, than those aged between 0 and 19 years. The likelihood of stopping testing was lower (HR 0.93, 95% CI 0.889-0.976) for the Asian group and higher for the Hispanic or Latino (HR 1.185, 95% CI 1.148-1.223) and Black or African American (HR 1.198, 95% CI 1.054-1.350) groups than the White group. CONCLUSIONS: The unique features of a pandemic response program that supported community-wide access to free asymptomatic testing provide a unique opportunity to evaluate adherence to testing recommendations and testing trends over time. Identification of individual and group-level factors associated with testing behaviors can provide insights for identifying potential areas of improvement in future testing initiatives.

The impact of delayed diagnosis and treatment due to COVID-19 on Australian thyroid cancer patients: a qualitative interview study.

OBJECTIVES: The study aims to investigate the perceptions of patients with thyroid cancer on the potential impact of diagnosis and treatment delays during the COVID-19 pandemic. DESIGN: This study involved qualitative semi-structured telephone interviews. The interviews were transcribed verbatim, analysed using the thematic framework analysis method and reported using the Consolidated Criteria for Reporting Qualitative Research. SETTING: Participants in the study were treated and/or managed at hospital sites across New South Wales and Victoria, Australia. PARTICIPANTS: 17 patients with thyroid cancer were interviewed and included in the analysis (14 females and 3 males). RESULTS: The delays experienced by patients ranged from <3 months to >12 months. The patients reported about delays to diagnostic tests, delays to surgery and radioactive iodine treatment, perceived disease progression and, for some, the financial burden of choosing to go through private treatment to minimise the delay. Most patients also reported not wanting to experience delays any longer than they did, due to unease and anxiety. CONCLUSIONS: This study highlights an increased psychological burden in patients with thyroid cancer who experienced delayed diagnosis and/or treatment during COVID-19. The impacts experienced by patients during this time may be similar in the case of other unexpected delays and highlight the need for regular clinical review during delays to diagnosis or treatment.

Clinical accuracy of instrument-based SARS-CoV-2 antigen diagnostic tests: a systematic review and meta-analysis.

BACKGROUND: During the COVID-19 pandemic, antigen diagnostic tests were frequently used for screening, triage, and diagnosis. Novel instrument-based antigen tests (iAg tests) hold the promise of outperforming their instrument-free, visually-read counterparts. Here, we provide a systematic review and meta-analysis of the SARS-CoV-2 iAg tests' clinical accuracy. METHODS: We systematically searched MEDLINE (via PubMed), Web of Science, medRxiv, and bioRxiv for articles published before November 7th, 2022, evaluating the accuracy of iAg tests for SARS-CoV-2 detection. We performed a random effects meta-analysis to estimate sensitivity and specificity and used the QUADAS-2 tool to assess study quality and risk of bias. Sub-group analysis was conducted based on Ct value range, IFU-conformity, age, symptom presence and duration, and the variant of concern. RESULTS: We screened the titles and abstracts of 20,431 articles and included 114 publications that fulfilled the inclusion criteria. Additionally, we incorporated three articles sourced from the FIND website, totaling 117 studies encompassing 95,181 individuals, which evaluated the clinical accuracy of 24 commercial COVID-19 iAg tests. The studies varied in risk of bias but showed high applicability. Of 24 iAg tests from 99 studies assessed in the meta-analysis, the pooled sensitivity and specificity compared to molecular testing of a paired NP swab sample were 76.7% (95% CI 73.5 to 79.7) and 98.4% (95% CI 98.0 to 98.7), respectively. Higher sensitivity was noted in individuals with high viral load (99.6% [95% CI 96.8 to 100] at Ct-level ≤ 20) and within the first week of symptom onset (84.6% [95% CI 78.2 to 89.3]), but did not differ between tests conducted as per manufacturer's instructions and those conducted differently, or between point-of-care and lab-based testing. CONCLUSION: Overall, iAg tests have a high pooled specificity but a moderate pooled sensitivity, according to our analysis. The pooled sensitivity increases with lower Ct-values (a proxy for viral load), or within the first week of symptom onset, enabling reliable identification of most COVID-19 cases and highlighting the importance of context in test selection. The study underscores the need for careful evaluation considering performance variations and operational features of iAg tests.

A prospective observational cohort study of covid-19 epidemiology and vaccine seroconversion in South Western Sydney, Australia, during the 2021-2022 pandemic period.

BACKGROUND: It is known that COVID-19 disproportionally adversely affects the immunocompromised, including kidney transplant recipients (KTR), as compared to the general population. Risk factors for adverse outcomes and vaccine seroconversion patterns are not fully understood. Australia was uniquely positioned to reduce initial case numbers during the 2021-2022 pandemic period due to its relative isolation and several significant public health interventions. South-Western Sydney Local Heath District was one of the predominant regions affected. METHODS: A single centre, prospective cohort study of prevalent renal transplant recipients was conducted between 25th July 2021 and 1st May 2022. Baseline characteristics, COVID-19 vaccination status, COVID-19 diagnosis and outcomes were determined from the electronic medical record, Australian vaccination register and Australian and New Zealand Dialysis and Transplant Registry. Assessment of vaccine-induced seroconversion was assessed with ELISA in a subpopulation. Analysis was performed using SPSS v.28. RESULTS: We identified 444 prevalent transplant recipients (60% male, 50% diabetic, median age 58 years (Interquartile range (IQR)21.0) and eGFR 56 ml/min/1.73m2 (IQR 21.9). COVID-19 was identified in 32% (n = 142) of patients, of which 38% (n = 54) required hospitalisation and 7% (n = 10) died. At least one COVID-19 vaccination was received by 95% (n = 423) with 17 (4%) patients remaining unvaccinated throughout the study period. Seroconversion after 2 and 3 doses of vaccine was 22% and 48% respectively. Increased COVID-19 related deaths were associated with older age (aOR 1.1, 95% CI 1.004-1.192, p = 0.040), smoking exposure (aOR 8.2, 05% CI 1.020-65.649, p = 0.048) and respiratory disease (aOR 14.2, 95%CI:1.825-110.930, p = 0.011) on multi-variable regression analysis. Receipt of three doses of vaccination was protective against acquiring COVID-19 (aOR 0.48, 95% CI 0.287-0.796, p = 0.005) and death (aOR 0.6, 95% CI: 0.007-0.523, p = 0.011), but not against hospitalisation (p = 0.32). Seroconversion was protective for acquiring COVID-19 on multi-variable regression independent of vaccination dose (aOR 0.1, 95%CI: 0.0025-0.523, p = 0.011). CONCLUSIONS: COVID-19 was associated with a high mortality rate. Older age, respiratory disease and prior smoking exposure may be risk factors for increased mortality. Vaccination of 3 doses is protective against acquiring COVID-19 and death, however not hospitalisation. Antibody response is protective for acquiring COVID-19, however seroconversion rates are low.

Rapid Nucleic Acid Diagnostic Technology for Pandemic Diseases.

The recent global pandemic of coronavirus disease 2019 (COVID-19) has enormously promoted the development of diagnostic technology. To control the spread of pandemic diseases and achieve rapid screening of the population, ensuring that patients receive timely treatment, rapid diagnosis has become the top priority in the development of clinical technology. This review article aims to summarize the current rapid nucleic acid diagnostic technologies applied to pandemic disease diagnosis, from rapid extraction and rapid amplification to rapid detection. We also discuss future prospects in the development of rapid nucleic acid diagnostic technologies.

Wastewater based epidemiology as a surveillance tool during the current COVID-19 pandemic on a college campus (East Carolina University) and its accuracy in predicting SARS-CoV-2 outbreaks in dormitories.

The COVID-19 outbreak led governmental officials to close many businesses and schools, including colleges and universities. Thus, the ability to resume normal campus operation required adoption of safety measures to monitor and respond to COVID-19. The objective of this study was to determine the efficacy of wastewater-based epidemiology as a surveillance method in monitoring COVID-19 on a college campus. The use of wastewater monitoring as part of a surveillance program to control COVID-19 outbreaks at East Carolina University was evaluated. During the Spring and Fall 2021 semesters, wastewater samples (N = 830) were collected every Monday, Wednesday, and Friday from the sewer pipes exiting the dormitories on campus. Samples were analyzed for SARS-CoV-2 and viral quantification was determined using qRT-PCR. During the Spring 2021 semester, there was a significant difference in SARS-CoV-2 virus copies in wastewater when comparing dorms with the highest number student cases of COVID-19 and those with the lowest number of student cases, (p = 0.002). Additionally, during the Fall 2021 semester it was observed that when weekly virus concentrations exceeded 20 copies per ml, there were new confirmed COVID-19 cases 85% of the time during the following week. Increases in wastewater viral concentration spurred COVID-19 swab testing for students residing in dormitories, aiding university officials in effectively applying COVID testing policies. This study showed wastewater-based epidemiology can be a cost-effective surveillance tool to guide other surveilling methods (e.g., contact tracing, nasal/salvia testing, etc.) to identify and isolate afflicted individuals to reduce the spread of pathogens and potential outbreaks within a community.

Characterizing participants who respond to text, email, phone calls, or postcards in a SARS-CoV-2 prevalence study.

INTRODUCTION: Multiple modalities and frequencies of contact are needed to maximize recruitment in many public health surveys. The purpose of this analysis is to characterize respondents to a statewide SARS-CoV-2 testing study whose participation followed either postcard, phone outreach or electronic means of invitation. In addition, we examine how participant characteristics differ based upon the number of contacts needed to elicit participation. METHODS: This is a cross-sectional analysis of survey data collected from participants who were randomly selected to represent Indiana residents and were invited to be tested for Covid-19 in April 2020. Participants received invitations via postcard, text/emails, and/or robocalls/texts based upon available contact information. The modality, and frequency of contacts, that prompted participation was determined by when the notification was sent and when the participant responded and subsequently registered to participate in the study. Chi square analyses were used to determine differences between groups and significant findings were analyzed using multinomial logistic regression. RESULTS: Respondents included 3,658 individuals and were stratified by postcards (7.9%), text/emails (26.5%), and robocalls/text (65.7%) with 19.7% registering after 1 contact, 47.9% after 2 contacts, and 32.4% after 3 contacts encouraging participation. Females made up 54.6% of the sample and responded at a higher rate for postcards (8.2% vs. 7.5%) and text/emails (28.1 vs. 24.6%) as compared to males (χ2 = 7.43, p = 0.025). Compared to males, females responded at a higher percentage after 1 contact (21.4 vs. 17.9%, χ2 = 7.6, p = 0.023). Those over 60 years responded most often after 2 contacts (χ2 = 27.5, p < 0.001) when compared to others at younger age groups. In regression analysis, participant sex (p = 0.036) age (p = 0.005), educational attainment (p = < 0.0001), and being motivated by "free testing" (p = 0.036) were correlated with participation in the prevalence study. DISCUSSION: Researchers should be aware that the modality of contact as well as the number of prompts used could influence differential participation in public health studies. Our findings can inform researchers developing studies that rely on selective participation by study subjects. We explore how to increase participation within targeted demographic groups using specific modalities and examining frequency of contact.

RNA-Based Sensor Systems for Affordable Diagnostics in the Age of Pandemics.

In the era of the COVID-19 pandemic, the significance of point-of-care (POC) diagnostic tools has become increasingly vital, driven by the need for quick and precise virus identification. RNA-based sensors, particularly toehold sensors, have emerged as promising candidates for POC detection systems due to their selectivity and sensitivity. Toehold sensors operate by employing an RNA switch that changes the conformation when it binds to a target RNA molecule, resulting in a detectable signal. This review focuses on the development and deployment of RNA-based sensors for POC viral RNA detection with a particular emphasis on toehold sensors. The benefits and limits of toehold sensors are explored, and obstacles and future directions for improving their performance within POC detection systems are presented. The use of RNA-based sensors as a technology for rapid and sensitive detection of viral RNA holds great potential for effectively managing (dealing/coping) with present and future pandemics in resource-constrained settings.

Artificial Neural Network Prediction of COVID-19 Daily Infection Count.

This study addresses COVID-19 testing as a nonlinear sampling problem, aiming to uncover the dependence of the true infection count in the population on COVID-19 testing metrics such as testing volume and positivity rates. Employing an artificial neural network, we explore the relationship among daily confirmed case counts, testing data, population statistics, and the actual daily case count. The trained artificial neural network undergoes testing in in-sample, out-of-sample, and several hypothetical scenarios. A substantial focus of this paper lies in the estimation of the daily true case count, which serves as the output set of our training process. To achieve this, we implement a regularized backcasting technique that utilize death counts and the infection fatality ratio (IFR), as the death statistics and serological surveys (providing the IFR) as more reliable COVID-19 data sources. Addressing the impact of factors such as age distribution, vaccination, and emerging variants on the IFR time series is a pivotal aspect of our analysis. We expect our study to enhance our understanding of the genuine implications of the COVID-19 pandemic, subsequently benefiting mitigation strategies.

Inferring COVID-19 testing and vaccination behavior from New Jersey testing data.

Characterizing the relationship between disease testing behaviors and infectious disease dynamics is of great importance for public health. Tests for both current and past infection can influence disease-related behaviors at the individual level, while population-level knowledge of an epidemic's course may feed back to affect one's likelihood of taking a test. The COVID-19 pandemic has generated testing data on an unprecedented scale for tests detecting both current infection (PCR, antigen) and past infection (serology); this opens the way to characterizing the complex relationship between testing behavior and infection dynamics. Leveraging a rich database of individualized COVID-19 testing histories in New Jersey, we analyze the behavioral relationships between PCR and serology tests, infection, and vaccination. We quantify interactions between individuals' test-taking tendencies and their past testing and infection histories, finding that PCR tests were disproportionately taken by people currently infected, and serology tests were disproportionately taken by people with past infection or vaccination. The effects of previous positive test results on testing behavior are less consistent, as individuals with past PCR positives were more likely to take subsequent PCR and serology tests at some periods of the epidemic time course and less likely at others. Lastly, we fit a model to the titer values collected from serology tests to infer vaccination trends, finding a marked decrease in vaccination rates among individuals who had previously received a positive PCR test. These results exemplify the utility of individualized testing histories in uncovering hidden behavioral variables affecting testing and vaccination.

Comparison of the Clinical Outcomes Between Early and Delayed Transplantation After SARS-CoV-2 Infection.

Our study analyzed 95 solid organ transplant (SOT) and 78 hematopoietic stem cell transplant (HSCT) recipients with prior coronavirus disease 2019 (COVID-19). Patients who underwent transplantation within 30 days of COVID-19 infection comprised the early group, and those who underwent transplantation post-30 days of COVID-19 infection comprised the delayed group. In the early transplantation group, no patient, whether undergoing SOT and HSCT, experienced COVID-19-associated complications. In the delayed transplantation group, one patient each from SOT and HSCT experienced COVID-19-associated complications. Additionally, among early SOT and HSCT recipients, two and six patients underwent transplantation within seven days of COVID-19 diagnosis, respectively. However, no significant differences were observed in the clinical outcomes of these patients compared to those in other patients. Early transplantation following severe acute respiratory syndrome coronavirus 2 infection can be performed without increased risk of COVID-19-associated complications. Therefore, transplantation needs not be delayed by COVID-19 infection.

Impact of the COVID-19 pandemic on the real-world diagnostic infrastructure for tuberculosis-An ESGMYC collaborative study.

We determined the impact of the COVID-19 pandemic on mycobacterial diagnostic services. 40 laboratories from 22 countries completed an online questionnaire covering the redeployment of the laboratory infrastructure and/or staff for SARS-CoV-2 testing, staff shortages and supply chain disruptions. 28 laboratories reported monthly numbers of samples processed for mycobacterial investigations and monthly numbers of M. tuberculosis complex (MTBC) PCRs performed between October 1st 2018 and October 31st 2020. More than half (23/40) of the participating TB laboratories reported having performed COVID-19 diagnostics in the early phase of the pandemic, in part with negative impact on the mycobacterial service activities. All participating laboratories reported shortages of consumables and laboratory equipment due to supply chain issues. Average monthly sample numbers decreased by 24% between January 2020 and October 2020 compared to pre-pandemic averages. At the end of the study period, most participating laboratories had not returned to pre-pandemic average MTBC PCR throughput.

Use of artificial intelligence to develop predictive algorithms of cough and PCR-confirmed COVID-19 infections based on inputs from clinical-grade wearable sensors.

There have been over 769 million cases of COVID-19, and up to 50% of infected individuals are asymptomatic. The purpose of this study aimed to assess the use of a clinical-grade physiological wearable monitoring system, ANNE One, to develop an artificial intelligence algorithm for (1) cough detection and (2) early detection of COVID-19, through the retrospective analysis of prospectively collected physiological data from longitudinal wear of ANNE sensors in a multicenter single arm study of subjects at high risk for COVID-19 due to occupational or home exposures. The study employed a two-fold approach: cough detection algorithm development and COVID-19 detection algorithm development. For cough detection, healthy individuals wore an ANNE One chest sensor during scripted activity. The final performance of the algorithm achieved an F-1 score of 83.3% in twenty-seven healthy subjects during biomarker validation. In the COVID-19 detection algorithm, individuals at high-risk for developing COVID-19 because of recent exposures received ANNE One sensors and completed daily symptom surveys. An algorithm analyzing vital parameters (heart rate, respiratory rate, cough count, etc.) for early COVID-19 detection was developed. The COVID-19 detection algorithm exhibited a sensitivity of 0.47 and specificity of 0.72 for detecting COVID-19 in 325 individuals with recent exposures. Participants demonstrated high adherence (≥ 4 days of wear per week). ANNE One shows promise for detection of COVID-19. Inclusion of respiratory biomarkers (e.g., cough count) enhanced the algorithm's predictive ability. These findings highlight the potential value of wearable devices in early disease detection and monitoring.

Target sign in COVID-19, radiological interpretation and diagnostic contribution of digital thoracic tomosynthesis.

INTRODUCTION: Our objectives are: To describe the radiological semiology, clinical-analytical features and prognosis related to the target sign (TS) in COVID-19. To determine whether digital thoracic tomosynthesis (DTT) improves the diagnostic ability of radiography. MATERIAL AND METHODS: Retrospective, descriptive, single-centre, case series study, accepted by our ethical committee. Radiological, clinical, analytical and follow-up characteristics of patients with COVID-19 and TS on radiography and DTT between November 2020 and January 2021 were analysed. RESULTS: Eleven TS were collected in 7 patients, median age 35 years, 57% male. All TS presented with a central nodule and a peripheral ring, and in at least 82%, the lung in between was of normal density. All TS were located in peripheral, basal regions and 91% in posterior regions. TS were multiple in 43%. Contiguous TS shared the peripheral ring. Other findings related to pneumonia were associated in 86% of patients. DTT detected 82% more TS than radiography. Only one patient underwent a CT angiography of the pulmonary arteries, positive for acute pulmonary thromboembolism. Seventy-one per cent presented with pleuritic pain. No distinctive laboratory findings or prognostic worsening were detected. CONCLUSIONS: TS in COVID-19 predominates in peripheral and declining regions and can be multiple. Pulmonary thromboembolism was detected in one case. It occurs in young people, frequently with pleuritic pain and does not worsen the prognosis. DTT detects more than 80 % of TS than radiography.

Changes in diagnostic patterns and resource utilisation in Swiss adult ICUs during the first two COVID-19 waves: an exploratory study.

BACKGROUND AND AIM: The coronavirus disease 2019 (COVID-19) outbreak deeply affected intensive care units (ICUs). We aimed to explore the main changes in the distribution and characteristics of Swiss ICU patients during the first two COVID-19 waves and to relate these figures with those of the preceding two years. METHODS: Using the national ICU registry, we conducted an exploratory study to assess the number of ICU admissions in Switzerland and their changes over time, characteristics of the admissions, the length of stay (LOS) and its trend over time, ICU mortality and changes in therapeutic nursing workload and hospital resources in 2020 and compare them with the average figures in 2018 and 2019. RESULTS: After analysing 242,935 patient records from all 84 certified Swiss ICUs, we found a significant decrease in admissions (-9.6%, corresponding to -8005 patients) in 2020 compared to 2018/2019, with an increase in the proportion of men admitted (61.3% vs 59.6%; p <0.001). This reduction occurred in all Swiss regions except Ticino. Planned admissions decreased from 25,020 to 22,021 in 2020 and mainly affected the neurological/neurosurgical (-14.9%), gastrointestinal (-13.9%) and cardiovascular (-9.3%) pathologies. Unplanned admissions due to respiratory diagnoses increased by 1971 (+25.2%), and those of patients with acute respiratory distress syndrome (ARDS) requiring isolation reached 9973 (+109.9%). The LOS increased by 20.8% from 2.55 ± 4.92 days (median 1.05) in 2018/2019 to 3.08 ± 5.87 days (median 1.11 days; p <0.001), resulting in an additional 19,753 inpatient days. The nine equivalents of nursing manpower use score (NEMS) of the first nursing shift (21.6 ± 9.0 vs 20.8 ± 9.4; p <0.001), the total NEMS per patient (251.0 ± 526.8 vs 198.9 ± 413.8; p <0.01) and mortality (5.7% vs 4.7%; p <0.001) increased in 2020. The number of ICU beds increased from 979 to 1012 (+3.4%), as did the number of beds equipped with mechanical ventilators (from 773 to 821; +6.2%). CONCLUSIONS: Based on a comprehensive national data set, our report describes the profound changes triggered by COVID-19 over one year in Swiss ICUs. We observed an overall decrease in admissions and a shift in admission types, with fewer planned hospitalisations, suggesting the loss of approximately 3000 elective interventions. We found a substantial increase in unplanned admissions due to respiratory diagnoses, a doubling of ARDS cases requiring isolation, an increase in ICU LOS associated with substantial nationwide growth in ICU days, an augmented need for life-sustaining therapies and specific therapeutic resources and worse outcomes.